Open AccessCohort Analysis and Reporting for Graduate Attribute Assessment
Author(s) -
Aneta George,
Liam Peyton
Publication year - 2018
Publication title -
proceedings of the ... ceea conference
Language(s) - English
Resource type - Journals
ISSN - 2371-5243
DOI - 10.24908/pceea.v0i0.13020
Subject(s) - cohort , medical education , graduate students , computer science , data collection , cohort study , engineering management , psychology , data science , mathematics education , statistics , engineering , medicine , mathematics
The Graduate Attribute Information Analysis system (GAIA) was developed at the University of Ottawa to support data collection and performance management of graduate attributes for engineering programs at the program level and at the course level [10]. This paper reports on our research to develop support for cohort analysis and reporting by providing a single consistent view of graduate attributes (GA) and performance indicators for groups of students who started and finished an engineering program at the same time. This is supported by two special purpose reports: Graduate Attribute Report per Cohort (GAR/C) and Course Progression Report per Cohort (CPR/C). The former shows average GA data per attribute, the latter tracks student achievement as students progress in their program. It also adds to the historic data trend analysis for a program. Furthermore, a COOP Progress Report per cohort (COOPR/C) is generated.